4 citations · 6 across the 8 of their papers we have counts for
8 papers
Zero-Shot Contextual Embeddings via Offline Synthetic Corpus Generation
Philip Lippmann, Jie Yang
Context-aware embedding methods boost retrieval accuracy by conditioning on corpus statistics (e.g., term co-occurrence and topical patterns) extracted from neighboring documents.…
Style over Substance: Distilled Language Models Reason Via Stylistic Replication
Philip Lippmann, Jie Yang
Specialized reasoning language models (RLMs) have demonstrated that scaling test-time computation through detailed reasoning traces significantly enhances performance. Although the…
Context-Informed Machine Translation of Manga using Multimodal Large Language Models
Philip Lippmann, Konrad Skublicki, Joshua Tanner +2
Due to the significant time and effort required for handcrafting translations, most manga never leave the domestic Japanese market. Automatic manga translation is a promising poten…
Positive Experience Reflection for Agents in Interactive Text Environments
Philip Lippmann, Matthijs T. J. Spaan, Jie Yang
Intelligent agents designed for interactive environments face significant challenges in text-based games, a domain that demands complex reasoning and adaptability. While agents bas…
Illuminating Blind Spots of Language Models with Targeted Agent-in-the-Loop Synthetic Data
Philip Lippmann, Matthijs T. J. Spaan, Jie Yang
Language models (LMs) have achieved impressive accuracy across a variety of tasks but remain vulnerable to high-confidence misclassifications, also referred to as unknown unknowns…
Red Teaming for Large Language Models At Scale: Tackling Hallucinations on Mathematics Tasks
Aleksander Buszydlik, Karol Dobiczek, Michał Teodor Okoń +3
We consider the problem of red teaming LLMs on elementary calculations and algebraic tasks to evaluate how various prompting techniques affect the quality of outputs. We present a…
How do you feel? Measuring User-Perceived Value for Rejecting Machine Decisions in Hate Speech Detection
Philippe Lammerts, Philip Lippmann, Yen-Chia Hsu +2
Hate speech moderation remains a challenging task for social media platforms. Human-AI collaborative systems offer the potential to combine the strengths of humans' reliability and…
A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities
Andrea Tocchetti, Lorenzo Corti, Agathe Balayn +4
Despite the impressive performance of Artificial Intelligence (AI) systems, their robustness remains elusive and constitutes a key issue that impedes large-scale adoption. Robustne…